code: def mock_load(filepath: str) -> Tuple[Tensor, int]:
      audio_rate = 1024
      outputs = torch.ones([1, audio_rate], dtype=torch.float) / 255
      for i, elem in enumerate(filepath):
          outputs[:, i] = int(elem) / 256
      return outputs, audio_rate
  
file_path: ml-cvnets/tests/data/datasets/audio_classification/test_speech_commands_v2.py
imports: import argparse
  from typing import Tuple
  from unittest import mock
  import pytest
  import torch
  from torch import Tensor
  from data.collate_fns import collate_functions
  from data.datasets.audio_classification.speech_commands_v2 import SpeechCommandsv2Dataset
label_desc: Use image node_id 1 for calling a global function with example usage: mock_load(filepath) and returns: outputs,  audio_rate